A Study on the Use of a Binary Local Descriptor and Color Extensions of Local Descriptors for Video Concept Detection

  • Foteini Markatopoulou
  • Nikiforos Pittaras
  • Olga Papadopoulou
  • Vasileios Mezaris
  • Ioannis Patras
Conference paper

DOI: 10.1007/978-3-319-14445-0_25

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8935)
Cite this paper as:
Markatopoulou F., Pittaras N., Papadopoulou O., Mezaris V., Patras I. (2015) A Study on the Use of a Binary Local Descriptor and Color Extensions of Local Descriptors for Video Concept Detection. In: He X., Luo S., Tao D., Xu C., Yang J., Hasan M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8935. Springer, Cham

Abstract

In this work we deal with the problem of how different local descriptors can be extended, used and combined for improving the effectiveness of video concept detection. The main contributions of this work are: 1) We examine how effectively a binary local descriptor, namely ORB, which was originally proposed for similarity matching between local image patches, can be used in the task of video concept detection. 2) Based on a previously proposed paradigm for introducing color extensions of SIFT, we define in the same way color extensions for two other non-binary or binary local descriptors (SURF, ORB), and we experimentally show that this is a generally applicable paradigm. 3) In order to enable the efficient use and combination of these color extensions within a state-of-the-art concept detection methodology (VLAD), we study and compare two possible approaches for reducing the color descriptor’s dimensionality using PCA. We evaluate the proposed techniques on the dataset of the 2013 Semantic Indexing Task of TRECVID.

Keywords

Video feature extraction concept detection concept-based video retrieval binary descriptors 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Foteini Markatopoulou
    • 1
    • 2
  • Nikiforos Pittaras
    • 1
  • Olga Papadopoulou
    • 1
  • Vasileios Mezaris
    • 1
  • Ioannis Patras
    • 2
  1. 1.CERTHInformation Technologies Institute (ITI)ThermiGreece
  2. 2.Queen Mary University of LondonUK

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